Making The Invisible Visible - Li Huang's Story
ByWater Institute's researcher Li Huang shares her life's work, from China to The Gulf Coast.
When Li Huang talks about the place she grew up, she doesn’t start with people or food or even buildings. She starts with geology.
"The river cut deep into the mountains—almost a thousand meters. You could see layers of rock from millions of years ago just sitting there, like a natural museum," she told me. That river was the Yangtze, and the city was Yichang, home to the world-famous Three Gorges Dam. Huang calls it "the hydropower capital of the world."
It's easy to see how someone raised in that place might grow up with a deep curiosity about water. For Huang, that interest eventually became a profession. Today, she works as a research scientist at the ByWater Institute at Tulane University, specializing in groundwater modeling, hydrogeology, and the growing use of machine learning in environmental science.
But the path to New Orleans wasn’t direct. After completing her undergraduate degree in China, she moved to Russia as part of an elite program that sent top students abroad. There, she earned a master’s degree at Moscow State University under the guidance of one of the country's leading eco-geologists. "He started the whole department," she said. "I was lucky to study with him."
She wrote her thesis in Russian. She traveled to Lake Baikal and the Black Sea. She read Chekhov and visited the towns where her favorite authors were born. It was beautiful, she said, and also difficult.
Later, a teacher in China connected her with Professor Cheng, a prominent researcher in the U.S. known for his work on contaminant transport in groundwater. She read his papers, got in touch, and started a collaboration that would eventually bring her to the University of Alabama, where Cheng was based at the time.
Now at Tulane, Huang’s work focuses on groundwater modeling—a field that straddles geology, chemistry, physics, and computer science. Groundwater isn’t something most people see, but it's an essential part of life in the Gulf South, supplying drinking water, sustaining ecosystems, and buffering against saltwater intrusion and drought.
"People think of water as rivers and lakes," Huang said. "But there's also water under the ground, in rock and soil. That's groundwater. And when it interacts with surface water, things get complicated."
To understand those interactions, Huang builds complex models that simulate how water moves through underground systems. These models are based on mathematical equations, informed by hydrological and geological data, and increasingly shaped by new tools from computer science.
"Numerical models are like equations broken into Lego blocks," she explained. "Machine learning can help us fit those blocks together faster and better, especially when there's too much data for a person to handle."
The models she builds help guide major environmental decisions. In one past project, she worked with USGS data to study how agricultural nitrate pollution in Alabama moved through groundwater and into the Gulf of Mexico. Today, her main focus is the Brazos River Basin in Texas, where she collaborates with researchers at Arizona State University and other institutions to study water availability, drought resilience, and agricultural impacts. Her role centers on groundwater, while others model surface water or land use.
"Eventually, I think we'll have models that can simulate the whole Earth’s water system and update themselves automatically as new data comes in," she said. "It sounds like science fiction, but I think it's just a matter of time."
That future may be closer than it seems. Machine learning is already being used in everything from flood forecasting to crop planning, but applying it to groundwater—and to the partial differential equations that govern water flow underground—remains a cutting-edge challenge. Huang is developing hybrid models that combine physical and data-driven approaches. "Each one has its strengths," she said. "And together, they can do more."
Despite the high-level work, she doesn’t see herself as especially ambitious. "I just follow what interests me," she said with a laugh. That approach has taken her from central China to Moscow, to Alabama, and now to New Orleans.
When asked what she finds most rewarding about research, she paused before answering. "It's the process of trying to figure things out," she said. "It takes time, but it's worth it."
At ByWater, her work may be technical, but the motivation is simple: understanding something invisible, and making it visible for the sake of resilience.
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